A National Science Foundation (NSF) project is underway with researchers at the University of Delaware, the Cold Regions Research and Engineering Laboratory, the Australian Antarctic Division, the National Ice Center (NIC) and Clarkson University to evaluate NIC weekly ice charts against in situ sea-ice thickness observations (see figure below). The goal is to ascertain their quality for use in monitoring sea-ice thickness and mass balance changes in the Southern Ocean. This initial project focuses on the Ross Sea region during the time period of 1995 to 2000.
Sea-ice thickness is calculated for both datasets. The datasets are then temporally joined with spatially averaged in situ (point) observations matching their respective NIC ice chart (polygon) analysis using a geographic information system (GIS). The uncertainties of total ice thickness for both in situ observations and NIC ice charts are propagated through individual calculations and the GIS tools.
Our preliminary findings suggest the potential usefulness of the NIC data to develop a regional sea-ice climatology in the comparison with coincident NIC ice charts and ship-based observations in the Ross Sea during five separate time periods through both the growth and decay seasons. The NIC data resolves the seasonal cycle of sea-ice thickness and extent with evident interannual variability between years. For example, greater ice thickness is observed in 1995 versus 1998 while a greater sea-ice extent is found in 1998 in comparison to 1995. A detailed examination of sea-ice thickness and variability during the 1995 to 1998 period will be investigated in our presentation and paper.
A GIS web site is also under development for online visualization and distribution of the in situ sea-ice observations from the Antarctic Sea Ice Processes and Climate (ASPECT) program and satellite-derived National Ice Center weekly ice charts. This GIS web application is being built using the new Environmental Systems Research Institute’s (ESRI) ArcGIS Server to display thickness estimates and their respective uncertainties, along with capabilities to spatially and temporally query the datasets to view and subset time periods and geographic areas of interest. The goal is to serve the sea-ice and climate modeling communities.
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